Pathfollowingvarianter

Pathfollowingvarianter (path-following variants) describe a family of control strategies that aim to keep a vehicle or agent close to a predefined geometric path, prioritizing path geometry over strict timing. The path can be represented as a polyline, spline, or polynomial curve, and controllers generate actuation commands to minimize cross-track and along-track error. Path-following is commonly contrasted with trajectory tracking, which also enforces timing constraints.

Common variants include pure pursuit, which steers toward a look-ahead point on the path; the Stanley variant, which combines lateral path error with heading error through a steering model; and model predictive path following, which optimizes a short-horizon cost along the path while respecting dynamics and constraints. Other approaches use vector fields, feedback linearization, or learning-based methods to produce path-conforming commands. Variants can differ in how they parameterize the path (time-parameterized versus distance-parameterized), how they measure error, and how aggressively they correct deviations.

Implementation considerations include path representation and smoothing, handling curvature limits, and integrating speed control with the path. Real-time obstacle avoidance and occasional re-planning are often incorporated to improve robustness. Applications span autonomous ground vehicles, aerial drones, service robots, and computer animation, where staying on or near a designated route is desirable for safety, efficiency, or realism.

Evaluation focuses on tracking accuracy, stability, convergence speed, robustness to disturbances, and computational burden. The choice among pathfollowingvarianter depends on system dynamics, sensor quality, and the required balance between simplicity and performance. See also path tracking, trajectory planning, and model predictive control.